Datamesh Load Datasource

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Adds real behavioral context beyond the readOnlyHint/openWorldHint annotations: gridded sources open lazily with no data download, tabular sources download only under an inline size limit, and oversize tabular data must go through query_data. It does not quantify the limit or describe failure behavior when a tabular source is too large and no query is issued.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences, front-loaded with the core action, then the type-specific behavior and the fallback path. No filler or restatement of the name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values need not be explained, and the description covers both datasource classes and the oversize fallback. The only remaining gap is the unquantified size limit and what a caller observes when a tabular source is skipped.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single datasource_id parameter, so the baseline is 3. The description adds no syntax, format, or ID-provenance detail beyond what the schema already documents.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ("Summarize an entire datasource") and further splits behavior by datasource type (gridded vs tabular), which lets an agent scope it precisely. It names the sibling query_data as the alternative for large tabular data, though it does not contrast with other nearby siblings like datamesh_get_datasource_info.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit context: use this for whole-datasource summarization, and switch to query_data with filters when a tabular datasource exceeds the inline size limit. No explicit "do not use when" clause for gridded/tabular edge cases, but the routing condition is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.